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xlm-roberta-large-finetuned-lener_br-finetuned-lener-br

This model is a fine-tuned version of Luciano/xlm-roberta-large-finetuned-lener_br on the lener_br dataset. It achieves the following results on the evaluation set:

  • Loss: nan
  • Precision: 0.9122
  • Recall: 0.9163
  • F1: 0.9142
  • Accuracy: 0.9826

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.068 1.0 3914 nan 0.6196 0.8604 0.7204 0.9568
0.0767 2.0 7828 nan 0.8270 0.8710 0.8484 0.9693
0.0257 3.0 11742 nan 0.7243 0.9005 0.8029 0.9639
0.0193 4.0 15656 nan 0.9010 0.8984 0.8997 0.9821
0.0156 5.0 19570 nan 0.7150 0.9121 0.8016 0.9641
0.0165 6.0 23484 nan 0.7640 0.8796 0.8177 0.9691
0.0225 7.0 27398 nan 0.8851 0.9098 0.8973 0.9803
0.016 8.0 31312 nan 0.9081 0.9015 0.9048 0.9792
0.0078 9.0 35226 nan 0.8941 0.8863 0.8902 0.9788
0.0061 10.0 39140 nan 0.9026 0.9002 0.9014 0.9804
0.0057 11.0 43054 nan 0.8793 0.9018 0.8904 0.9769
0.0044 12.0 46968 nan 0.8790 0.9033 0.8910 0.9785
0.0043 13.0 50882 nan 0.9122 0.9163 0.9142 0.9826
0.0003 14.0 54796 nan 0.9032 0.9070 0.9051 0.9807
0.0025 15.0 58710 nan 0.8903 0.9085 0.8993 0.9798

Framework versions

  • Transformers 4.23.1
  • Pytorch 1.12.1+cu113
  • Datasets 2.6.1
  • Tokenizers 0.13.1
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Dataset used to train Luciano/xlm-roberta-large-finetuned-lener_br-finetuned-lener-br

Evaluation results